2024
Personalizing the empiric treatment of gonorrhea using machine learning models
Murray-Watson R, Grad Y, St. Cyr S, Yaesoubi R. Personalizing the empiric treatment of gonorrhea using machine learning models. PLOS Digital Health 2024, 3: e0000549. PMID: 39141668, PMCID: PMC11324139, DOI: 10.1371/journal.pdig.0000549.Peer-Reviewed Original ResearchGonococcal Isolate Surveillance ProjectTreatment of gonorrheaEmpirical treatmentAntimicrobial-resistantNational surveillance systemEffects of first-line therapyEmpirical treatment of gonorrhoeaPrevalence of antimicrobial-resistantPrevalence of resistant strainsStandard guidelinesFirst-line therapyResistant to ciprofloxacinFirst-line antibioticsRecommended first-line antibioticsEmergence of antimicrobial-resistantPatients' basic characteristicsStrains of Neisseria gonorrhoeaeSurveillance projectPrescribing effective treatmentCeftriaxoneGonorrheaRecommended treatmentEffective treatmentPersonalized treatmentCefixime
2022
Evaluating spatially adaptive guidelines for the treatment of gonorrhea to reduce the incidence of gonococcal infection and increase the effective lifespan of antibiotics
Yaesoubi R, Cohen T, Hsu K, Gift TL, St. Cyr SB, Salomon JA, Grad YH. Evaluating spatially adaptive guidelines for the treatment of gonorrhea to reduce the incidence of gonococcal infection and increase the effective lifespan of antibiotics. PLOS Computational Biology 2022, 18: e1009842. PMID: 35139073, PMCID: PMC8863219, DOI: 10.1371/journal.pcbi.1009842.Peer-Reviewed Original ResearchConceptsIncidence of gonorrhoeaTreatment guidelinesResistance prevalenceGonorrhea casesTreatment of gonorrheaNational surveillance systemPrevalence of resistanceTransmission dynamic modelGonococcal infectionGonorrhea treatmentMSM populationAntibiotic susceptibilityGonorrheaStandardized guidelinesSurveillance dataPrevalenceIncidenceAntibioticsPotential strategySurveillance systemAbsence of pointsGuidelinesCurrent strategiesEffective lifespanMen